Effects of non-health-targeted policies on migrant health: a systematic review and meta-analysis

Summary Background Government policies can strongly influence migrants' health. Using a Health in All Policies approach, we systematically reviewed evidence on the impact of public policies outside of the health-care system on migrant health. Methods We searched the PubMed, Embase, and Web of Science databases from Jan 1, 2000, to Sept 1, 2017, for quantitative studies comparing the health effects of non-health-targeted public policies on migrants with those on a relevant comparison population. We searched for articles written in English, Swedish, Danish, Norwegian, Finnish, French, Spanish, or Portuguese. Qualitative studies and grey literature were excluded. We evaluated policy effects by migration stage (entry, integration, and exit) and by health outcome using narrative synthesis (all included studies) and random-effects meta-analysis (all studies whose results were amenable to statistical pooling). We summarised meta-analysis outcomes as standardised mean difference (SMD, 95% CI) or odds ratio (OR, 95% CI). To assess certainty, we created tables containing a summary of the findings according to the Grading of Recommendations Assessment, Development, and Evaluation. Our study was registered with PROSPERO, number CRD42017076104. Findings We identified 43 243 potentially eligible records. 46 articles were narratively synthesised and 19 contributed to the meta-analysis. All studies were published in high-income countries and examined policies of entry (nine articles) and integration (37 articles). Restrictive entry policies (eg, temporary visa status, detention) were associated with poor mental health (SMD 0·44, 95% CI 0·13–0·75; I2=92·1%). In the integration phase, restrictive policies in general, and specifically regarding welfare eligibility and documentation requirements, were found to increase odds of poor self-rated health (OR 1·67, 95% CI 1·35–1·98; I2=82·0%) and mortality (1·38, 1·10–1·65; I2=98·9%). Restricted eligibility for welfare support decreased the odds of general health-care service use (0·92, 0·85–0·98; I2=0·0%), but did not reduce public health insurance coverage (0·89, 0·71–1·07; I2=99·4%), nor markedly affect proportions of people without health insurance (1·06, 0·90–1·21; I2=54·9%). Interpretation Restrictive entry and integration policies are linked to poor migrant health outcomes in high-income countries. Efforts to improve the health of migrants would benefit from adopting a Health in All Policies perspective

Institutional and behaviour-change interventions to support COVID-19 public health measures: a review by the Lancet Commission Task Force on public health measures to suppress the pandemic

The Lancet COVID-19 Commission Task Force for Public Health Measures to Suppress the Pandemic was launched to identify critical points for consideration by governments on public health interventions to control coronavirus disease 2019 (COVID-19). Drawing on our review of published studies of data analytics and modelling, evidence synthesis and contextualisation, and behavioural science evidence and theory on public health interventions from a range of sources, we outline evidence for a range of institutional measures and behaviour-change measures. We cite examples of measures adopted by a range of countries, but especially jurisdictions that have, thus far, achieved low numbers of COVID-19 deaths and limited community transmission of severe acute respiratory syndrome coronavirus 2. Finally, we highlight gaps in knowledge where research should be undertaken. As countries consider long-term measures, there is an opportunity to learn, improve the response and prepare for future pandemics

How Well Does Societal Mobility Restriction Help Control the COVID-19 Pandemic? Evidence from Real-Time Evaluation

One of the most widely implemented policy response to the novel coronavirus (SARS-CoV-2) pandemic has been the imposition of restrictions on mobility (1). These restrictions have included both incentives, encouraging working from home, supported by a wide range of online activities such as meetings, lessons, and shopping, and sanctions, such as stay at home orders, restrictions on travel, and closure of shops, offices, and public transport (2-5). The measures constitute a major component of efforts to control the COVID-19 pandemic. Compared to previous epidemic responses, they are unprecedented in both scale and scope (6). The rationale underpinning these public health measures is that restricting normal activities decreases the number, duration, and proximity of interpersonal contacts and thus the potential for viral transmission. Transmission simulations using complex mathematical modelling have built on past experience such as the 1918 influenza epidemic (7), as well as assumptions about the contemporary scale and nature of contact in populations (8). However, the initial models were not always founded on empirical evidence from behavioral scientists on the feasibility or sustainability of mass social and behavior change in contemporary society. While reductions in interpersonal contact and increases in physical distancing are known to decrease respiratory infection spread (9), the paucity of recent examples of large-scale restrictions on mobility has limited the scope for research on their impact on transmission. Where restrictions have been imposed, as with Ebola, they have involved diseases with a different mode of transmission. Nonetheless, the rapidity of progression of this pandemic has forced many governments into trialing various approaches to containment with limited evidence of effectiveness (10). More conventional public health prevention measures (such as quarantine of contacts, isolation of infected individuals and contact tracing) and control measures in health systems (such as patient flow segregation, negative pressure ventilation, and use of personal protective equipment) (11-14), have been applied widely to control the epidemic in many countries as part of a portfolio of policy responses. However, mobility restriction as a new large-scale mass behavioral and social prescription has incurred considerable costs (15, 16). Estimates suggest global GDP growth has fallen by as much as 10% (17), at least in part due to mobility restriction policies. Although views differ, not least because of the lack of information of what would happen if the disease was unchecked and the emerging evidence of persisting disability in survivors, some have argued that this is greater than would be accounted for by the economic impact of direct illness and deaths from COVID-19 (18, 19). To inform decisions on large scale restrictions of mobility, there is an urgent need to assess their effectiveness in limiting pandemic spread. To this end, we examined the association of mobility with COVID-19 incidence in Organization of Economic Cooperation and Development (OECD) countries and equivalent economies such as Singapore and Taiwan

Assessment of variation in the alberta context tool: the contribution of unit level contextual factors and specialty in Canadian pediatric acute care settings

Background: There are few validated measures of organizational context and none that we located are parsimonious and address modifiable characteristics of context. The Alberta Context Tool (ACT) was developed to meet this need. The instrument assesses 8 dimensions of context, which comprise 10 concepts. The purpose of this paper is to report evidence to further the validity argument for ACT. The specific objectives of this paper are to: (1) examine the extent to which the 10 ACT concepts discriminate between patient care units and (2) identify variables that significantly contribute to between-unit variation for each of the 10 concepts. Methods: 859 professional nurses (844 valid responses) working in medical, surgical and critical care units of 8 Canadian pediatric hospitals completed the ACT. A random intercept, fixed effects hierarchical linear modeling (HLM) strategy was used to quantify and explain variance in the 10 ACT concepts to establish the ACT’s ability to discriminate between units. We ran 40 models (a series of 4 models for each of the 10 concepts) in which we systematically assessed the unique contribution (i.e., error variance reduction) of different variables to between-unit variation. First, we constructed a null model in which we quantified the variance overall, in each of the concepts. Then we controlled for the contribution of individual level variables (Model 1). In Model 2, we assessed the contribution of practice specialty (medical, surgical, critical care) to variation since it was central to construction of the sampling frame for the study. Finally, we assessed the contribution of additional unit level variables (Model 3). Results: The null model (unadjusted baseline HLM model) established that there was significant variation between units in each of the 10 ACT concepts (i.e., discrimination between units). When we controlled for individual characteristics, significant variation in the 10 concepts remained. Assessment of the contribution of specialty to between-unit variation enabled us to explain more variance (1.19% to 16.73%) in 6 of the 10 ACT concepts. Finally, when we assessed the unique contribution of the unit level variables available to us, we were able to explain additional variance (15.91% to 73.25%) in 7 of the 10 ACT concepts. Conclusion: The findings reported here represent the third published argument for validity of the ACT and adds to the evidence supporting its use to discriminate patient care units by all 10 contextual factors. We found evidence of relationships between a variety of individual and unit-level variables that explained much of this between-unit variation for each of the 10 ACT concepts. Future research will include examination of the relationships between the ACT’s contextual factors and research utilization by nurses and ultimately the relationships between context, research utilization, and outcomes for patients

BMC Psychiatry

BACKGROUND: Suicidal ideation and suicidal risk assessment are major concerns for health professionals. The perception of a low level of parental support is a risk factor for suicidal tendencies among adolescents, but little is known about its long-term impact on the vulnerability to suicidal behavior in young adults. We investigated whether the perceived level of parental support during childhood and adolescence was associated with current suicidal ideation in young adults. METHODS: We retrieved data collected in the i-Share study from February 1st, 2013 through January 30, 2017. This cross-sectional study included 10,015 French students, aged 18-24 years that completed an on-line self-reported questionnaire about suicidal ideation in the last 12 months and their perceived parental support in childhood and adolescence. We performed multinomial logistic regressions and sensitivity analyses to assess associations between the degree of perceived parental support and the frequency suicidal thoughts, after adjusting for the main known risk factors of suicidal ideation. We employed multiple imputations to account for missing data. RESULTS: The study sample included 7539 female (75.7%) and 2436 male (24.3%) students (mean [SD] age 20.0 [1.8] years). About one in five students reported occasional suicidal thoughts (n = 1775, 17.7%) and 368 students (3.7%) reported frequent suicidal thoughts. The adjusted multinomial logistic regression revealed a significant negative association between perceived parental support and suicidal thoughts. A lack of perceived parental support in childhood and adolescence was associated with > 4-fold elevated risk of occasional (adjusted OR, 4.55; 95% CI: 2.97-6.99) and nearly 9-fold elevated risk of frequent (adjusted OR, 8.58; 95% CI: 4.62-15.96) suicidal thoughts, compared to individuals that perceived extremely strong parental support. This association was strongest among students with no personal history of depression or suicide attempts. CONCLUSIONS: Students that perceived low levels of past parental support had a higher risk of suicidal ideation. Past perceived parental support appeared to be a potent marker of suicidal risk in young adults. This marker should be routinely collected in studies on suicidal risk in young adults, and it could be considered an additional screening tool